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Earthcube

Earthcube

Deep Learning Scientist - Research-

  • Permanent contract 
  • Starting date:  
  • Paris-9e-Arrondissement
  • Master's Degree
  • > 3 years

The company

Earthcube

Earthcube

  • From 15 to 50 employees

The job

Deep Learning Scientist - Research-

  • Permanent contract 
  • Paris-9e-Arrondissement

About

At Earthcube, we are passionate about solving impossible problems! We believe that AI can positively change the way we work by removing repetitive and monotonous tasks, letting you focus on what really matters: providing meaning and context to the information.
That’s why we are developing monitoring solutions based on an automated analysis of satellites imagery for defence and intelligence customers. We bring our clients strategic knowledge regarding critical sites of interest, thus enabling faster interventions for a safer environment.
So if you want to join the adventure and push forward the limits of AI, look no further, you’ve found your tribe!

Job description

You will join the AI team to test new techniques in Deep Learning and adapt them to our use-cases, mostly linked to object detection and image segmentation. You will be part of a dedicated team that constantly watches the latest scientific papers and technological posts and implement the best solutions to improve our processes and our products.
It means that you will learn from experts in the dedicated AI team and that you will work on state-of-the-art topics in the field of deep learning. You will collaborate closely with our AI framework team to transform innovative and smart ideas into tools usable by everyone in the AI team. You will also work with both our internal business experts to understand the needs of our clients, and our data management team to access our vast database of labeled satellite images and expand it, if needed .

Your tasks will include:

  • Monitoring the latest advances in computer vision and deep learning
  • Designing experimental protocols to test cutting-edge techniques in domains such as few-shots learning, continuous and active learning, hierarchical learning, model ensembling…
  • Implementing and refining methods from scientific articles, git repositories or other publications to make them usable on our use-cases, and possibly work closely with the AI framework team to integrate them into production
  • Coming up with new ideas to push beyond state-of-the-art solutions
  • Writing scientific articles to submit to world-class conferences (CVPR, NeurIPS…)
  • Contributing to the specifications of our AI framework to improve the productivity of the whole AI team
  • Work closely with the GIS team and business experts to understand the data available and use it in the best possible ways

Preferred experience

We are looking for an open-minded individual with impressive skills and a proven track record. The skills listed below are key to be up to this challenge.

The must-haves:

  • Education in the field of computer vision / deep learning (Master degree, ideally PhD)
  • At least 3 years of experience in deep learning (including internships, online courses, personal side projects, PhD years)
  • Very good understanding of DL techniques, especially CNNs for Segmentation and Object Detection
  • Good skills in Python or other object-oriented languages
  • Strong experience in technology monitoring and scientific papers reading
  • Rigorous, creative and meticulous mind
  • Excellent organizational skills, autonomy, and reporting capabilities.
  • Willingness to take on challenges, show resiliency and like to always learn new skills

The nice-to-haves:

  • Strong knowledge in classical Computer Vision
  • Proficiency with docker
  • Experience working with remote sensing images
  • Experience working in a startup environment

Recruitment process

  • Call by one member of the team
  • Technical Challenge
  • F2F with the line manager, CTO, HR

Meet the Earthcube team

Earthcube

Earthcube

Deep Learning Scientist - Research-

  • Permanent contract 
  • Starting date:  
  • Paris-9e-Arrondissement
  • Master's Degree
  • > 3 years
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